Evaluation of the effectiveness of the cultural industry in the regions of Russia on the basis of DEA | Tomsk State University Journal of Cultural Studies and Art History. 2021. № 44. DOI: 10.17223/22220836/44/6

Evaluation of the effectiveness of the cultural industry in the regions of Russia on the basis of DEA

According to the results of the evaluation of the activities of theater institutions in accordance with the DEA model, the regions with the highest level of efficiency of functioning and the leading regions in terms of evaluating the activities of museums, effective regions for the activities of concert organizations and independent collectives were identified. These regions demonstrate an effective structure and return on financing the costs of their activities. Analyzing the experience of leaders for each selected region-leader, exploring the main parameters of their activities, it is possible to assess the possibility of applying their work experience in the current environment. The proposed assessment of the technical efficiency of the regions from the point of view of the functioning of the basic types of cultural institutions can be interpreted as a relative indicator of the quality of management. This makes it possible to compare the levels of efficiency of the functioning of cultural institutions at the regional level. The results of using the proposed model provide a more detailed and objective picture of the evaluation of the effectiveness of cultural institutions. DEA-analysis allows us to determine the direction of the search for constructive solutions in the management system, when developing plans and monitoring activities as an effective tool for modeling competitive, sustainable and balanced socio-economic development of the region. The identification of the most and least effective regions and types of cultural institutions that require special attention in development policy allows us to draw conclusions based on interregional comparisons that will help determine the target areas of support for the cultural industry.

Download file

Counter downloads: 36

Keywords

enterprises of the industry of culture, theatres, museums, concert organization, efficiency, Data Envelopment Analysis (DEA)

Authors

Name	Organization	E-mail
Malshina Nataliya A.	Saratov state conservatory named after L. V. Sobinov	malsnataliya@yandex.ru
Firsova Anna A.	Saratov national research State University named after N. G. Chernyshevsky	a.firsova@rambler.ru
Chernyshova Galina Yu.	Saratov national research State University named after N. G. Chernyshevsky	cherny111@mail.ru

Всего: 3

References

The Russian Federal Service of State Statistics [Rosstat]. URL http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/en/statistics/science_and_innovations/science/#

Malshina N., Firsova A. Mechanisms of Innovative Projects Financing in the Culture Industry on the Basis of Public-private Partnership // Proceedings of the 3rd International Conference on Judicial, Administrative and Humanitarian Problems of State Structures and Economic Subjects (JAHP 2018). Series: Advances in Social Science, Education and Humanities Research (ASSEHR), vol. 252, p. 100-105. https://www.atlantis-press.com/proceedings/jahp-18/25902084

Malshina N., Firsova A. Mechanism of financing the project activities of the creative industries in the Russian Federation. Proceedings of the International Scientific Conference “Far East Con” (ISCFEC 2018) https://www.atlantis-press.com/proceedings/iscfec-18/Proceedings of the International Scientific Conference “Far East Con” (ISCFEC 2018) Part of series: AEBMR, ISSN: 2352-5428, vol. 47 ISBN 978-94-6252-656-3

Castelli L., Pesenti R., Ukovich W. A classification of DEA models when the internal structure of the Decision Making Units is considered // Ann Oper Res. 2010. Vol. 173. P. 207-235. https://doi.org/10.1007/s10479-008-0414-2 of DEA models when the internal structure of decision making units is considered //European Journal of Operational Research. 2010. № 132. P. 274-286.

Tone K. Advances in DEA Theory and Applications: With Extensions to Forecasting Models. New York : John Wiley & Sons, 2017. 576 p.

Zhu J. Data Envelopment analysis: Handbook of Empirical Studies and Applications. New York : Springer, 2016. 587 p.

Liu J., Lu L. A survey of DEA applications // Omega. 2013. Vol. 41(5). P. 893-902.

Cook W., Tone K., Zhu J. Data envelopment analysis: Prior to choosing model // Omega. 2014. Vol. 44. P. 1-4.

Cheng G., Qian Z. MaxDEA manual. Peking University. Beijing, China, 2011. 275 p.

Charnes A., Cooper W.W., Rhodes E. Measuring the efficiency of decision making units // European Journal of Operational Research. 1978. Vol. 2, № 6. P. 429-444.

Banker R.D., Charnes A., Cooper W.W. Some models for estimating technical and scale inefficiencies in data envelopment analysis // Management Science. 1984. Vol. 30, № 9. P. 10781092.

Cheng G., Zervopoulos P.D. Estimating the technical efficiency of health care systems: A cross-country comparison using the directional distance function // European Journal of Operational Research. 2014. Vol. 238, № 3. P. 899-910.

Главный информационно-вычислительный центр Министерства культуры Российской Федерации. URL: https://stat.mkrf.ru/indicators/

Cooper W., Seiford L., Tone K. Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software. Boston : Kluwer Academic Publishers, 2007. 318 p.